Multivariate survival data under bivariate frailty: An estimating equation approach

被引：9

作者：

Xue, XN ^{[1
]}

机构：

[1] SUNY Albany, Sch Publ Hlth, Dept Biometry & Stat, Rensselaer, NY 12144 USA

来源：

BIOMETRICS | 1998年 / 54卷 / 04期

关键词：

heterogeneity; Poisson formulation; quasi-likelihood;

D O I：

10.2307/2533687

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

A modified frailty model is developed to improve the computing efficiency of the bivariate frailty model proposed by Xue and Brookmeyer (1996, Lifetime Data Analysis 2, 277-290) for the analysis of multivariate survival data. Originally, the frailty was modeled parametrically and a modified EM approach was used to estimate the parameters of interest, however, with intensive computations. The modified frailty model formulates a Poisson regression model and applies quasi-likelihood estimating equations to estimate the parameters of interest. This procedure not only significantly reduces the computation but also avoids using a parametric assumption for the frailty distribution. Simulation studies show the estimators perform well. The method is also applied to a mental health care dataset.

引用

页码：1631 / 1637

页数：7